Examples
Worked examples
- Is an instance
A research institution cites GIDA-published guidance when drafting its Indigenous data policy.
- Is an instance
A funder references GIDA's CARE Principles in its data management plan requirements.
Counter-examples
Looks similar, but isn't
- Not an instance
An organisation that merely studies Indigenous communities without Indigenous leadership is not GIDA.
- Not an instance
A national open-data initiative without Indigenous engagement is not aligned with GIDA's mission.
Editorial commentary
The Global Indigenous Data Alliance brings together regional Indigenous data sovereignty networks and individual scholars and practitioners. GIDA has authored foundational documents including the CARE Principles, contributes to international forums on data governance and FAIR/CARE alignment, and provides a platform for Indigenous-led articulation of data rights. GIDA’s authority in this domain is widely recognised within research data governance communities.
Founding and member networks
GIDA was established at a workshop held 11–12 July 2019 at the International Institute for the Sociology of Law in Oñati, Spain, convened by Maggie Walter and Desi Rodriguez-Lonebear and bringing together Indigenous data governance researchers and practitioners from multiple countries. Its founding member networks were the United States Indigenous Data Sovereignty Network (USIDSN), Te Mana Raraunga — the Māori Data Sovereignty Network (Aotearoa New Zealand) — and the Maiam nayri Wingara Collective (Australia). GIDA’s own stated position is that national and regional Indigenous Data Sovereignty networks are best placed to progress data sovereignty for their own peoples and communities, with the global alliance coordinating shared vision, tools, and advocacy across them rather than acting as a single centralised authority.
The CARE Principles
GIDA’s best-known output is the CARE Principles for Indigenous Data Governance — Collective Benefit, Authority to Control, Responsibility, Ethics — published in September 2019 and formally set out in peer-reviewed form the following year (Carroll, S.R., Garba, I., Figueroa-Rodríguez, O.L. et al., “The CARE Principles for Indigenous Data Governance,” Data Science Journal, 19(1):43, 2020). CARE was deliberately designed to complement, not replace, the FAIR Principles for scientific data (Findable, Accessible, Interoperable, Reusable): FAIR is oriented toward the technical and infrastructural properties of data, while CARE is oriented toward the people and purpose the data serves and the rights Indigenous Peoples hold over data about themselves, their knowledge, and their territories. See CASRAI’s CARE Principles entry and the CARE vs. FAIR comparison for the full principle-by-principle breakdown.
How GIDA relates to other bodies and frameworks
GIDA is organisationally distinct from, but works alongside, the Research Data Alliance’s International Indigenous Data Sovereignty Interest Group; its work is referenced and hosted alongside RDA’s own materials as an affiliated organisation, and the two have co-convened joint sessions and workshops. GIDA is likewise distinct from — though its work is frequently cited together with — nationally specific frameworks: Canada’s OCAP Principles (First Nations Information Governance Centre, First-Nations-specific) and Australia’s AIATSIS Code of Ethics (which covers the research relationship as a whole, not data governance specifically). Attributing the CARE Principles to a body other than GIDA, or treating GIDA, OCAP, and AIATSIS as one interchangeable framework, is a sourcing error worth avoiding — each represents a distinct, Indigenous-led governance initiative with its own scope and origin.
References
- GIDA, “Who We Are” and CARE Principles for Indigenous Data Governance (2019), gida-global.org
- Carroll, S.R. et al., “The CARE Principles for Indigenous Data Governance,” Data Science Journal, 19(1):43 (2020)
Related: CARE Principles · OCAP Principles · Te Mana Raraunga · Maiam nayri Wingara · Indigenous Data Sovereignty · FPIC.
Also known as
GIDA
Machine-readable encodings
Use in your systems
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